The human brain can rewire itself after a traumatic bodily injury, researchers report. Similar findings have been previously reported in animal studies, but this is one of the first studies where such a result has been documented in people.

https://news.missouri.edu/2019/talk-to-the-hand/

Do Deep Neural Networks ‘See’ Faces Like Brains Do?

https://medium.com/syncedreview/do-deep-neural-networks-see-faces-like-brains-do-dc3eef334d79

A deeper dive into UMAP theory
Andy Coenen, Adam Pearce : https://pair-code.github.io/understanding-umap/supplement.html
#ArtificialIntelligence #DeepLearning #MachineLearning

When Artificial Intelligence gets FUNNY with an ability to detect humour & predict LAUGHTER using multimodal language dataset, named UR-FUNNY.
It demonstrated the role of context & punchline in humour detection using TED Talk transcripts with laughter cues for humour analysis.

#EMNLP2019
Read: https://arxiv.org/pdf/1904.06618.pdf
GitHub: https://github.com/ROC-HCI/UR-FUNNY

Learning to Predict Without Looking Ahead: World Models Without Forward Prediction

Rather than hardcoding forward prediction, we try to get agents to *learn* that they need to predict the future.

Check out our #NeurIPS2019 paper!

https://learningtopredict.github.io
https://arxiv.org/abs/1910.13038

NeurIPS 2019: Adversarial music that prevents Amazon Alexa from waking up

https://www.profillic.com/paper/arxiv:1911.00126
They target the attack on the wake-word detection system, jamming the model with some inconspicuous background music to deactivate the VAs while the audio adversary is present

TOP AI & MACHINE LEARNING RESEARCH PAPERS FROM 2019
https://www.topbots.com/top-ml-research-papers-2019/

Query2vec: Search query expansion with query embeddings
https://bytes.grubhub.com/search-query-embeddings-using-query2vec-f5931df27d79

The Measure of Intelligence
François Chollet : https://arxiv.org/abs/1911.01547
GitHub : https://github.com/fchollet/ARC
#ArtificialIntelligence #DeepLearning #MachineLearning

Dynamics-Aware Unsupervised Discovery of Skills
Sharma et al.: https://arxiv.org/abs/1907.01657
#MachineLearning #Robotics #ReinforcementLearning

Deep learning reveals cancer metastasis and therapeutic antibody targeting in whole body
https://www.biorxiv.org/content/biorxiv/early/2019/02/05/541862.full.pdf

A GPT-2 style model for dialog
A State-of-the-Art Large-scale Pretrained Response generation model (DialoGPT)
code https://github.com/microsoft/DialoGPT
paper https://arxiv.org/pdf/1911.00536.pdf

AI meets physics - using artificial neural networks to approximate solutions of the three-body problem.


I'm increasingly intrigued by this paper (https://arxiv.org/pdf/1910.07291.pdf) showing the application of Artificial Neural networks to the infamously insoluble three-body problem in physics, where we try to work out the future position of three objects sometime in the future given Newton's equations of motion. I think it has important implications to how we think about approximation and how we achieve it in practice.

From the authors: "Our results provide evidence that, for computationally challenging regions of phase-space, a trained ANN can replace existing numerical solvers, enabling fast and scalable simulations of many-body systems to shed light on outstanding phenomena such as the formation of black-hole binary systems or the origin of the core collapse in dense star clusters."

https://t.iss.one/ArtificialIntelligenceArticles

5 challenges for the next 5 years of computer vision research by Jitendra Malik at ICCV2019

The latest from TensorFlow
Tensorflow 2.0
Transformers library
Up to 3x training performance improvement
Addons and extensions
Tensorboard, debugging and visualization
Tensorflow Hub: pretrained models
Deploy ML anywhere: TF-extended (server), TF-lite (mobile) and TF-js (web)

https://www.youtube.com/watch?v=n56syJSLouA